System and methods for diagnostic image analysis and image quality assessment

ABSTRACT

A method of analyzing and assessing an image comprises the steps of: (a) obtaining said image in a digital form; (b) processing said image; and (c) establishing at least one edge line within said image. The step of processing said image further includes: (a) building a 3D graph of intensity distribution within said image; (b) calculating identifying vector angle values (IVAVs); said angles adjoin to points of said 3D intensity distribution graph which correspond to individual pixels of said image; said angles lie in a plane defined by an intensity axis of said image; (c) setting a range of lower and upper thresh-hold level values (THLV1 and THLV2) between which edge points are indicatable; and (d) indicating edge points according to said THLV1 and THLV2.

RELATED APPLICATIONS

This application is a National Phase of PCT Patent Application No.PCT/IL2017/050391 having International filing date of Mar. 29, 2017,which claims the benefit of priority of U.S. Provisional Application No.62/315,715 filed on Mar. 31, 2016. The contents of the aboveapplications are all incorporated by reference as if fully set forthherein in their entirety.

FIELD OF THE INVENTION

The present invention relates generally to the field of image assessmentand analysis. More specifically, the present invention relates to anautomated image analysis and image quality assessment based on theextraction of predefined data from the input of images to be used forfurther analysis as accurate quantitative measurements and qualitativeinferences regarding individuals and classes of objects in the image.

BACKGROUND OF THE INVENTION

The following description includes information that may be useful inunderstanding the present invention. It is not an admission that any ofthe information provided herein is prior art or relevant to thepresently claimed invention, or that any publication specifically orimplicitly referenced is prior art.

Scientific endeavors generally require precise and accuratequantification to determine results. In medicine and in the field ofcardiology in particular, the results obtained from various tests areused in further decision-making regarding the patient including accuratediagnosis and treatment. Many tests, especially those involving imaging,provide results that require great skill to analyze by a trained expertor specialist. Due to the huge amount of information presented in animage and the lack of accurate fully automated systems for analysis, thefield of medicine is frequently left to semi-quantitation (e.g., gradeon a 1 to 4 scale). While this may be adequate for many purposes,observer bias, lack of reproducibility, and lack of the ability to beprecise often results in the need for more testing to try to be certainof the diagnosis, or painstaking effort by the physician to make surethe treatment is given in the effective regions (e.g., that the properlocation on the field of image is treated by X-rays, etc.). The abilityto perform rapid and accurate quantification using computer-assistedimage analysis can be a great aid in these fields.

Currently there have been great limitations in the full automation ofimage analysis. There are edge-detection system and methods availablethat look for a general change in the picture but generally requirenoise subtraction and input from a user to focus on the areas ofinterest or from an encyclopedic database to compare the image to inorder to identify or delimit the object of interest in the image. Theedges detected are generally based on first and second differentiationand are binary (edge present/absent) but not qualitative (do not reflectinformation about different types of edges present). Users of currentprocesses need frequent and direct operator input to effectuate ananalysis.

None of the current technologies and prior art, taken alone or incombination, address nor provide a utility solution for a fullyautomated precise image analysis and image quality assessment based onthe extraction of predefined data from the input of images using areal-time simultaneous technology. The present invention can identifyfine edges and distinguish between different objects without the need tomake assumptions about the input image or to use filters or noisereduction methods that result in a net loss of data.

Specific uses and applications of this process include the field ofcoronary angiography and echocardiography. The raw images obtained inthese arts including cineangiograms of the coronary arteries and echoimages of the cardiac chamber walls until presently have not readilybeen amenable to accurate fully automated analysis of artery caliber(diameter along its length to evaluate amount of stenosis) or chamberdimensions and wall thickness.

In coronary angiography until present the cardiologist has had toestimate the percent stenosis along the length of the artery as revealedby the gold standard coronary angiogram (luminogram) or by othertechniques including intravascular ultrasound or ComputerizedTomographic (CT) scan. However, actual automation of this analysis isburdensome and currently has been inaccurate and therefore unreliable.Using the new detection methods inside a larger method of straighteningthe artery so that perpendicular cuts are obtained for measurement isproviding the ability for both a fully automated and a more accurateanalysis of the whole length of the artery.

In echocardiography field, there is currently no fully automated methodof measuring cardiac chamber borders and dimensions. The input of thetechnologist is required in multiple steps of the image analysis. Thenew method is being developed to enable fully automated chambermeasurements and wall thickness analyses and ejection fractioncalculation. This would enable accurate noninvasive hemodynamic andcardiac output determinations.

Furthermore, great promise is expected in the field of artificialvision. By comparing two pictures temporally or side-by-side, with thefine resolution and discriminating abilities of the new method, thedistances and dimensions of objects will be quickly amenable tocalculation. By efficiently and automatically determining the shape andsize of the object, automated identification should be greatly improved.

Further uses include the field of CT and MRI (magnetic resonanceimaging) and ultrasound scans. The ability to accurately automaticallymeasure chamber edges is expected to allow for automated analysis ofnormal and abnormal and for generation and comparison to encyclopedicdatabase for further refinement of the art and science besides improvingdiagnosis and treatment for each individual patient. Another use wouldbe for automated identification and marking of an organ edge forradiation therapy, for example.

US 20130278776 discloses a method for automatic left ventricular (LV)inner border detection. The method comprises the steps of: performingimage mapping on an echocardiogram in order to produce a multi-levelimage map; converting the image map into a binary image by attributingpixels of one or more darker levels of the image map to the LV cavityand pixels of one or more lighter levels of the image map to themyocardium; applying a radial filter to contours of the myocardium inthe binary image, to extract an approximate inner border of the LV; andperforming shape modeling on the approximate inner border, to determinethe LV inner border.

It should be emphasized that precision of shape modelling of edge linesin binary images strongly depends on a dynamic range of the originalimage. The narrow dynamic range results in lower precision of obtainededge line. Thus, there is a long-felt and unmet need to provide a methodand a device that overcomes the problems associated with the prior art.

SUMMARY OF THE INVENTION

It is hence one object of the invention to disclose a method ofanalyzing and assessing an image. The aforesaid method comprises thesteps of: (a) obtaining said image in a digital form; (b) processingsaid image; and (c) establishing at least one edge line within saidimage.

It is a core purpose of the invention to provide the step of processingsaid image comprising: a) building a 3D graph of intensity distributionwithin said image; (b) calculating identifying vector angle values(IVAVs); said angles adjoin to points of said 3D intensity distributiongraph which correspond to individual pixels of said image; said angleslie in a plane defined by an intensity axis of said image; (c) setting arange of lower and upper thresh-hold level values (THLV1 and THLV2)between which edge line points are indicatable; and (d) tracing saidedge points according to said THLV1 and THLV2.

Another object of the invention is to disclose the step of processingsaid image comprising a sub-step of finding a central area ofventricular cavity carried out automatically or manually.

A further object of the invention is to disclose the step of tracingsaid edge line performed in polar coordinates with an origin positionedin said central area of ventricular cavity.

A further object of the invention is to disclose the step of tracingsaid edge line comprising a sub-step of finding discontinuitiesindicated by a jump of said IVAV and removing found discontinuities byconnecting the previously found fragments of said edge line adjacent tosaid discontinuities.

A further object of the invention is to disclose the step of tracingsaid edge line comprising a sub-step of forming borders of an objectselected from the group consisting of: epicardium and ventricularendocardium, of the left or right heart in the image and any combinationthereof.

A further object of the invention is to disclose the boundaries ofobjects in an image which is an image obtained from a vehicle camerausable for identification of surrounding obstacles.

A further object of the invention is to disclose a step of calculatingof a characteristic selected from the group consisting of: a minimalwall thickness, an epicardial ventricular volume, an endocardialventricular volume, difference therebetween, and any combinationthereof.

A further object of the invention is to disclose the device foranalyzing and assessing an image. The aforesaid device comprises: (a) aunit configured for digital input of said image; (b) a processorconfigured for analyzing and assessing said image; (c) an interface unitconfigured for controlling said device and displaying processed imagesand contiguous data.

It is another core purpose of the invention to provide the processor isfurther configured for: (a) building a 3D graph of intensitydistribution within said image; (b) calculating identifying vector anglevalues (IVAVs); said angles adjoin to points of said 3D intensitydistribution graph which correspond to individual pixels of said image;said angles lie in a plane defined by an intensity axis of said image;(c) setting a range of lower and upper thresh-hold level values (THLV1and THLV2) between which edge points are indicatable; and (d) tracingsaid edge points according to said THLV1 and THLV2. A further object ofthe invention is to disclose a non-transitory computer-readable mediumhaving thereon software instructions configured to cause a processor toperform operations comprising: (a) obtaining said image in a digitalform; (b) establishing at least one edge line within said image.

It is another core purpose of the invention to provide the operation ofprocessing said image comprising: (a) building a 3D graph of intensitydistribution within said image; (b) calculating identifying vector anglevalues (IVAVs); said angles adjoin to points of said 3D intensitydistribution graph which correspond to individual pixels of said image;said angles lie in a plane defined by an intensity axis of said image;(c) setting a range of lower and upper thresh-hold level values (THLV1and THLV2) between which edge points are indicatable; and (d) tracingsaid edge points according to said THLV1 and THLV2.

BRIEF DESCRIPTION OF THE PREFERRED EMBODIMENTS

The novel features believed to be characteristics of the invention areset the appended claims. The invention itself, however, as well as thepreferred mode of use, further objects and advantages thereof, will bestbe understood by reference to the following detailed description ofillustrative embodiment when read in conjunction with the accompanyingdrawings, wherein:

FIG. 1 is a flowchart of a method of analyzing and assessing an image;

FIGS. 2a to 2e are schematic diagram explaining a procedure of scanningan image in polar coordinates and calculation of identifying vectorangle values; and

FIGS. 3a and 3b are exemplary processed echocardiographic images withclosed and open edge lines, respectively.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description is provided, so as to enable any personskilled in the art to make use of said invention and sets forth the bestmodes contemplated by the inventor of carrying out this invention.Various modifications, however, are adapted to remain apparent to thoseskilled in the art, since the generic principles of the presentinvention have been defined specifically to provide method, device andsoftware for analyzing and assessing an image.

The term “intensity” refers hereinafter to an intensity value of a grayscale image, an integral intensity value of a color image, an intensityvalue of a color selected image and combination thereof.

The term “image” refers hereinafter to any image in a digital formdescribable by a function of intensity distribution which includesrecognizable edge structures. For example, the present invention isapplicable to images captured by medical devices, surveillance camerasand alike.

Reference is now made to FIG. 1 presenting a flow chart of a method 100of for analyzing and assessing an image. The known procedure includesproviding the image to be analyzed and assessed in a digital form (step110), processing the provided images (step 120) and establishing atleast one edge line (step 130). In order to increase precision ofpinpointing the edge line, step 120 comprises building a 3D graph ofintensity distribution within the image (step 121). Then, at step 122,identifying vector angle values (IVAV) are calculated. The aforesaidangles adjoin to points of 3D intensity distribution graph whichcorrespond to individual pixels of the image. The angles to becalculated lie in a vertical plane defined by an intensity axis(ordinate axis). Any function of original intensity function, such asits integral or differential, or a linear or quadratic modification, orcombination of these, or other modifications or curves derived from theoriginal intensity function used for obtaining the IVAVs are in thescope of the present invention.

At step 123, criteria of indicating an edge line are set. Specifically,lower and upper thresh-hold level values (THLV1 and THLV2) define anangle range in which the edge line is indicatable. When the THLV1 andTHLV2 are applied to the calculated IVAVs, points meeting THLV1 andTHLV2 requirements are traced (step 124). Thus, the obtained points formthe sought-for edge line. IVAV and THLV expressed by means of anyfunction of the aforesaid angles such as its complement, supplement, orits sine or cosine or tangent are in the scope of the present invention,

Reference is now made to FIG. 2a explaining the abovementionedprocedure. The 3D graph of intensity distribution within the image (notshown) is placed into Cartesian coordinates (I, X, Y). Planes X=X₁ andY=Y₁ orthogonal to each other illustrate the process of scanning the 3Dgraph of intensity distribution in the polar coordinates. For eachintensity curve C₁/C₂ lying in planes X=X₁ and Y=Y₁, IVAVs arecalculated. Points P₀ to P₄ are the points on the 3D graph of intensitydistribution and correspond to the pixels of the image to be analyzed.Point P₀ belongs curves C₁ and C₂ lying to both X=X₁ and Y=Y₁. Points P₁and P₂ belong to C₁ lying in plane X=X₁ while P₃ and P₄ belong to C₂lying in plane Y=Y₁.

Reference is now made to FIGS. 2b and 2c illustrating calculation of anIVAV which is attributed to point P₀.

As seen in FIG. 2a , an Y-component of the IVAV of point P₀ Φ_(Y) isdefined as a reciprocal between slopes of tangent lines T₁ and T₂established in points P₁ and P₂ of curve C₁ corresponding to adjoiningpixels.

Solving right triangles with respect to the rule of angle signs, we havefor the Y-component:φ_(Y)=atan(δX ₁ /δI ₁)−atan(δX ₂ /δI ₂).

Referring to FIG. 2b , we have for the X-component:Φ_(X)=atan(δY ₁ /δI ₃)−atan(δY ₂ /δI ₄).

Reference is now made to FIG. 2d presenting a simplified approach tocalculation of IVAVs. Specifically, the tangent lines are replaced withthe lines interconnecting point P₀ with points P₁ and P₂. As definedabove, the IVAV attributed to P₀, is a difference between thearccotangent of the slopes of the intensity curve in points P₁ and P₂,in this case, between arccotangent of the slopes of line segments P₀P₁and P₀P₂.

The standard calculations give sought-for value Φ:

$\Phi = {{\overset{\_}{+}\arcsin}\;{\frac{\Delta\left( {I_{1} - I_{2}} \right)}{\sqrt{\left( {\Delta^{2} + I_{1}^{2}} \right)\left( {\Delta^{2} + I_{2}^{2}} \right)}}.}}$

If calculated angle Φ_(X) or Φ_(Y) falls within the predetermined anglerange between THLV1 and THLV2, pixel P₀ is indicated as an edge pixel. Agreater number of components of angle Φ than 2 is also in the scope ofthe present invention. Pixels meeting the aforesaid criterion form theedge line. According to one embodiment of the present invention, acertain type of edge is indicated in the specific pixel location in thepicture if either component Φ_(X) or Φ_(Y) falls between 0° and 15°.

According to an exemplary embodiment of the present invention, method,device and software for analyzing and assessing medical images isdisclosed. All considerations in the present application concerning theleft ventricle are equally applicable to the right ventricle.

Reference is now made to FIG. 2e illustrating calculation of an IVAVwhich is attributed to point M₀. Planes S₀, S₁ and S₂ correspond toscanning along R-axis at constant values of angle φ, specifically at φ0,φ1 and φ2, respectively. Similar to the previous consideration inCartesian coordinates, curves C₁ and C₂ intersect each other in pointM₀. Points M₁ and M₂ belong to curve C1. Points M₃ and M₄ belong tocurve C₂. Along with this, points M₁ and M₂ lie in plane S₀, points M₃in plane S₁ and M₄ in plane S₂.

Reference is now made to FIGS. 3a and 3b , presenting exemplaryprocessed echocardiographic images with closed and open edge lines,respectively. Referring to FIG. 2a , numeral 10 indicates anechocardiographic image. Edge line 20 borders a left ventricle of heart.Shown edge line 20 is closed.

From a practical standpoint, a median filter can be applied to the imageto be processed. Additionally, polar coordinates are more convenient forthe aforesaid procedure. The origin of coordinates is positioned into acentral area of the ventricular cavity. This operation can be carriedout automatically or manually. The center of the ventricular cavity canbe found as an area of minimal intensity within the echocardiographicimage.

Referring to FIG. 3b , edge line 25 is open. According to the presentinvention, discontinuities in the edge line should be found and closed.The discontinuities can arise in the area of an open valve.

The algorithm of forming the edge line enables calculating an area ofthe traced ventricular endocardium. On the basis of Simpson's formulaand presumption of conicity of the left ventricle, volume of the leftventricle can be calculated from obtained locations of apical andmidpoints on a 2D image. Building edge lines within 3D images is also inthe scope of the present invention.

The disclosed algorithm enables building boundaries not only the leftendocardium but also the right endocardium. Thus, a left ventricularwall, a right ventricular wall or pericardial sack can be evaluated.Similar, an actual wall thickness can be calculated across the wholeventricular septum, with a mean and standard deviation calculated andreported. The same can be performed for all the walls (lateral,inferior, anterior, etc.). Regions of relative thinning or thickeningcan be reported. Overall cardiac mass can be calculated using thedifference between the total LV volume (outer, epicardial) minus theinternal LV volume (endocardial).

In the case of synchronization of echocardiographic images with an EKGsignal and location of the R wave, end-diastole (ED) and end-systole(ES) volumes can be obtained. In addition, ED and ES volumes can bedetermined by comparing different frames for maximum and minimum LVvolume, respectively. The timing mark can be obtained from valve openingor closure (ED corresponds to the closed mitral valve while EScorresponds to the closed aortic valve and the open mitral valve). Thesevolumes can then be reported (as a plot against time, for example).

Reference throughout this specification to “one embodiment” or “anembodiment” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment of the present invention. Thus, theappearances of the phrases “in one embodiment” or “in an embodiment” invarious places throughout this specification are not necessarily allreferring to the same embodiment. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more embodiments.

While the technology will be described in conjunction with variousembodiment(s), it will be understood that they are not intended to limitthe present technology to these embodiments. On the contrary, thepresent technology is intended to cover alternatives, modifications andequivalents, which may be included within the spirit and scope of thevarious embodiments as defined by the appended claims.

Furthermore, in the following description of embodiments, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present technology. However, the present technologymay be practiced without these specific details. In other instances,well known methods, procedures, components, and circuits have not beendescribed in detail as not to unnecessarily obscure aspects of thepresent embodiments.

Unless specifically stated otherwise as apparent from the followingdiscussions, it is appreciated that throughout the present descriptionof embodiments, discussions utilizing terms such as “obtaining”,“calculating”, “processing”, “performing,” “extracting,” “configuring”or the like, refer to the actions and processes of a computer system, orsimilar electronic computing device. The computer system or similarelectronic computing device manipulates and transforms data representedas physical (electronic) quantities within the computer system'sregisters and memories into other data similarly represented as physicalquantities within the computer system memories or registers or othersuch information storage, transmission, or display devices, includingintegrated circuits down to and including chip level firmware,assembler, and hardware based micro code.

As will be explained in further detail below, the technology describedherein relates to generating, storing and using semantic networks anddatabases to correlate physiological and psychological states of usersand/or groups of users using their voice intonation data analysis.

While the invention is susceptible to various modifications andalternative forms, specific embodiments thereof have been shown by wayof example in the drawings and the above detailed description. It shouldbe understood, however, that it is not intended to limit the inventionto the particular forms disclosed, but on the contrary, the intention isto cover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the invention as defined by the appended claims.

In some embodiments, the illustrated system elements could be combinedinto a single hardware device or separated into multiple hardwaredevices. If multiple hardware devices are used, the hardware devicescould be physically located proximate to or remotely from each other.

The methods can be implemented in a computer program product accessiblefrom a computer-usable or computer-readable storage medium that providesprogram code for use by or in connection with a computer or anyinstruction execution system. A computer-usable or computer-readablestorage medium can be any apparatus that can contain or store theprogram for use by or in connection with the computer or instructionexecution system, apparatus, or device.

A data processing system suitable for storing and/or executing thecorresponding program code can include at least one processor coupleddirectly or indirectly to computerized data storage devices such asmemory elements. Input/output (I/O) devices (including but not limitedto keyboards, displays, pointing devices, etc.) can be coupled to thesystem. Network adapters may also be coupled to the system to enable thedata processing system to become coupled to other data processingsystems or remote printers or storage devices through interveningprivate or public networks. To provide for interaction with a user, thefeatures can be implemented on a computer with a display device, such asan LCD (liquid crystal display), virtual display, or another type ofmonitor for displaying information to the user, and a keyboard and aninput device, such as a mouse or trackball by which the user can provideinput to the computer. A computer program can be a set of instructionsthat can be used, directly or indirectly, in a computer. The systems andmethods described herein can be implemented using programming languagessuch as Flash™, JAVA™, C++, C, C#, Visual Basic™, JavaScript™, PHP, XML,HTML, etc., or a combination of programming languages, includingcompiled or interpreted languages, and can be deployed in any form,including as a stand-alone program or as a module, component,subroutine, or other unit suitable for use in a computing environment.The software can include, but is not limited to, firmware, residentsoftware, microcode, etc. Protocols such as SOAP/HTTP may be used inimplementing interfaces between programming modules. The components andfunctionality described herein may be implemented on any desktopoperating system executing in a virtualized or non-virtualizedenvironment, using any programming language suitable for softwaredevelopment, including, but not limited to, different versions ofMicrosoft Windows™, Apple™ Mac™, iOS™, Android™, Unix™/X-Windows™,Linux™, etc. The system could be implemented using a web applicationframework, such as Ruby on Rails.

The processing system can be in communication with a computerized datastorage system. The data storage system can include a non-relational orrelational data store, such as a MySQL™ or other relational database.Other physical and logical database types could be used. The data storemay be a database server, such as Microsoft SQL Server™, Oracle™, IBMDB2™, SQLITE™, or any other database software, relational or otherwise.The data store may store the information identifying syntactical tagsand any information required to operate on syntactical tags. In someembodiments, the processing system may use object-oriented programmingand may store data in objects. In these embodiments, the processingsystem may use an object-relational mapper (ORM) to store the dataobjects in a relational database. The systems and methods describedherein can be implemented using any number of physical data models. Inone example embodiment, an RDBMS can be used. In those embodiments,tables in the RDBMS can include columns that represent coordinates. Inthe case of environment tracking systems, data representing user events,virtual elements, etc. can be stored in tables in the RDBMS. The tablescan have pre-defined relationships between them. The tables can alsohave adjuncts associated with the coordinates.

Suitable processors for the execution of a program of instructionsinclude, but are not limited to, general and special purposemicroprocessors, and the sole processor or one of multiple processors orcores, of any kind of computer. A processor may receive and storeinstructions and data from a computerized data storage device such as aread-only memory, a random access memory, both, or any combination ofthe data storage devices described herein. A processor may include anyprocessing circuitry or control circuitry operative to control theoperations and performance of an electronic device.

The processor may also include, or be operatively coupled to communicatewith, one or more data storage devices for storing data. Such datastorage devices can include, as non-limiting examples, magnetic disks(including internal hard disks and removable disks), magneto-opticaldisks, optical disks, read-only memory, random access memory, and/orflash storage. Storage devices suitable for tangibly embodying computerprogram instructions and data can also include all forms of non-volatilememory, including, for example, semiconductor memory devices, such asEPROM, EEPROM, and flash memory devices; magnetic disks such as internalhard disks and removable disks; magneto-optical disks; and CD-ROM andDVD-ROM disks. The processor and the memory can be supplemented by, orincorporated in, ASICs (application-specific integrated circuits).

The systems, modules, and methods described herein can be implementedusing any combination of software or hardware elements. The systems,modules, and methods described herein can be implemented using one ormore virtual machines operating alone or in combination with each other.Any applicable virtualization solution can be used for encapsulating aphysical computing machine platform into a virtual machine that isexecuted under the control of virtualization software running on ahardware computing platform or host. The virtual machine can have bothvirtual system hardware and guest operating system software.

The systems and methods described herein can be implemented in acomputer system that includes a back-end component, such as a dataserver, or that includes a middleware component, such as an applicationserver or an Internet server, or that includes a front-end component,such as a client computer having a graphical user interface or anInternet browser, or any combination of them. The components of thesystem can be connected by any form or medium of digital datacommunication such as a communication network. Examples of communicationnetworks include, e.g., a LAN, a WAN, and the computers and networksthat form the Internet.

One or more embodiments of the invention may be practiced with othercomputer system configurations, including hand-held devices,microprocessor systems, microprocessor-based or programmable consumerelectronics, minicomputers, mainframe computers, etc. The invention mayalso be practiced in distributed computing environments where tasks areperformed by remote processing devices that are linked through anetwork.

The invention claimed is:
 1. A method of analyzing and assessing animage, said method comprising steps of: a. obtaining said image in aelectronic or digital form; b. processing said image; and c.establishing at least one edge line within said image; wherein said stepof processing said image comprises: a. building a 3D graph of intensitydistribution within said image; b. calculating identifying vector anglevalues (IVAVs); each angle adjoins to a point of said 3D intensitydistribution graph which corresponds to an individual pixel of saidimage; said angle lies in a plane defined by an intensity axis of saidimage and are formed by lines being tangent to said 3D graph ofintensity distribution located at nearest neighbor pixels to saidindividual pixel; c. setting a range of lower and upper thresh-holdlevel values (THLV1 and THLV2) between which edge points areindicatable; and d. indicating edge points according to said THLV1 andTHLV2.
 2. The method of claim 1, wherein at least one of the followingis true: a. said image is a medical image usable for diagnostics; b.said step of tracing said edge line comprises a sub-step of findingdiscontinuities indicated by a jump of said IVAV and removing founddiscontinuities by connecting the previously found fragments of saidedge line adjacent to said discontinuities.
 3. The method of claim 2,wherein said step of processing said image comprises a sub-step oflocating a central area of interest automatically or manually.
 4. Themethod of claim 3, wherein said step of tracing said edge line isperformed in polar coordinates with an origin positioned in said centralarea of ventricular cavity.
 5. The method of claim 2, wherein said stepof tracing said edge line comprises a sub-step for forming borders of anobject, the object selected in the heart from a group consisting ofepicardium, left ventricular endocardium, right epicardium anycombination thereof.
 6. The method of claim 2 comprising a step ofcalculating of a characteristic such as a minimal wall thickness, anepicardial ventricular volume, an endocardial ventricular volume,difference therebetween, and any combination thereof.
 7. The methodaccording to claim 1, wherein said image is an image obtained from avehicle camera usable for identification of surrounding obstacles.
 8. Adevice for analyzing and assessing an image; said device comprising: a.a unit configured for electronic or digital input of said image; b. aprocessor configured for analyzing and assessing said image; c. aninterface unit configured for controlling said device and displayingprocessed images and contiguous data; wherein said processor is furtherconfigured for: a. building a 3D graph of intensity distribution withinsaid image; b. calculating identifying vector angle values (IVAVs); eachangle adjoins to a point of said 3D intensity distribution graph whichcorresponds to an individual pixel of said image; said angle lies in aplane defined by an intensity axis of said image and are formed by linesbeing tangent to said 3D graph of intensity distribution located atnearest neighbor pixels to said individual pixel; c. setting a range oflower and upper thresh-hold level values (THLV1 and THLV2) between whichedge points are indicatable; and d. tracing said edge points accordingto said THLV1 and THLV2.
 9. The device of claim 8, wherein at least oneof the following is true: a. said image is a medical image usable fordiagnostics; and b. said processor is configured for findingdiscontinuities indicated by a jump of said IVAV and removing founddiscontinuities by connecting the previously found fragments of saidedge line adjacent to said discontinuities.
 10. The device of claim 9,wherein said processor is configured for finding a central area ofinterest carried out automatically or manually.
 11. The device of claim9, wherein said processor is configured for tracing said edge line inpolar coordinates with an origin positioned in said central area ofinterest.
 12. The device of claim 9, wherein said processor isconfigured for forming borders of an object selected from the groupconsisting of: epicardium, left ventricular endocardium, rightepicardium any combination thereof.
 13. The device of claim 9, whereinsaid processor is configured for calculating of a characteristicselected from the group consisting of: a minimal wall thickness, anepicardial-ventricular volume, an endocardial ventricular volume,difference therebetween, and any combination thereof.
 14. The device ofclaim 9, wherein said image is a medical image usable for diagnostics.15. A non-transitory computer-readable medium having thereon softwareinstructions configured to cause a processor to perform operationscomprising: a. obtaining said image in an electronic or digital form; b.establishing at least one edge line within said image; wherein saidoperation of processing said image comprises: a. building a 3D graph ofintensity distribution within said image; b. calculating identifyingvector angle values (IVAVs); each angle adjoins to a point of said 3Dintensity distribution graph which corresponds to an individual pixel ofsaid image; said angle lies in a plane defined by an intensity axis ofsaid image and are formed by lines being tangent to said 3D graph ofintensity distribution located at nearest neighbor pixels to saidindividual pixel; c. setting a range of lower and upper thresh-holdlevel values (THLV1 and THLV2) between which edge points areindicatable; and d. tracing said edge points according to said THLV1 andTHLV2.
 16. The non-transitory computer-readable medium of claim 15,wherein at least one of the following is true: a. said image is amedical image usable for diagnostics; b. the stored softwareinstructions is configured to cause a processor to perform said step oftracing said edge line comprising a sub-step of finding discontinuitiesindicated by a jump of said IVAV and removing found discontinuities byconnecting the previously found fragments of said edge line adjacent tosaid discontinuities.
 17. The non-transitory computer-readable medium ofclaim 16, wherein the stored software instructions is configured tocause a processor to perform said step of processing said imagecomprising a sub-step of finding a central area of ventricular cavitycarried out automatically or manually.
 18. The non-transitorycomputer-readable medium of claim 17, wherein the stored softwareinstructions is configured to cause a processor to perform said step oftracing said edge line in polar coordinates with an origin positioned insaid central area of ventricular cavity.
 19. The non-transitorycomputer-readable medium of claim 16, wherein the stored softwareinstructions is configured to cause a processor to perform said step oftracing said edge line comprising a sub-step for forming borders of anobject selected from the group consisting of; epicardium, leftventricular endocardium, right epicardium any combination thereof. 20.The non-transitory computer-readable medium of claim 16, wherein thestored software instructions is configured to cause a processor toperform a step of calculating of a characteristic such as thickness areaor volume in the heart selected from the group consisting of a minimalwall thickness, an epicardial ventricular volume, an endocardialventricular volume, difference therebetween, and any combinationthereof.